By Topic

Iris matching using multi-dimensional artificial neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
R. M. Farouk ; Department of Mathematics, Faculty of Science, Zagazig University, Egypt ; R. Kumar ; K. A. Riad

Iris recognition is one of the most widely used biometric technique for personal identification. This identification is achieved in this work by using the concept that, the iris patterns are statistically unique and suitable for biometric measurements. In this study, a novel method of recognition of these patterns of an iris is considered by using a multi-dimensional artificial neural network. The proposed technique has the distinct advantage of using the entire resized iris as an input at once. It is capable of excellent pattern recognition properties as the iris texture is unique for every person used for recognition. The system is trained and tested using two publicly available databases (CASIA and UBIRIS). The proposed approach shows significant promise and potential for improvements, compared with the other conventional matching techniques with regard to time and efficiency of results.

Published in:

IET Computer Vision  (Volume:5 ,  Issue: 3 )